US11687321B2 - System and method for valuating patent using multiple regression model and system and method for building patent valuation model using multiple regression model - Google Patents
System and method for valuating patent using multiple regression model and system and method for building patent valuation model using multiple regression model Download PDFInfo
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- US11687321B2 US11687321B2 US16/199,703 US201816199703A US11687321B2 US 11687321 B2 US11687321 B2 US 11687321B2 US 201816199703 A US201816199703 A US 201816199703A US 11687321 B2 US11687321 B2 US 11687321B2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/216—Parsing using statistical methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0278—Product appraisal
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/18—Legal services; Handling legal documents
- G06Q50/184—Intellectual property management
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- the present invention relates to a system and method for building a patent valuation model used to calculate a quantified valuation result of a patent and calculating a quantified valuation result of a patent using the patent valuation model, and more particularly, to a system and method for valuating a patent using a multiple regression model and a system and method for building a patent valuation model using a multiple regression model.
- intellectual property right holders personally grade their intellectual property rights or have their intellectual property rights graded by commercial or noncommercial organizations through patent technology valuation.
- Such patent valuation generally includes experts' valuation and automatic valuation.
- Experts' valuation is a method in which a patent is valuated by an expert of the corresponding technical field.
- expert knowledge of an individual expert may be used, and qualitative valuation is possible.
- the valuation is likely to be seriously affected by the expert's opinion, and much cost and time are required.
- the present invention is directed to providing a system and method for building a patent valuation model using a multiple regression model and a system and method for valuating a patent using a multiple regression model, the systems and methods making it possible to build a highly reliable valuation model, which does not only reflect structural characteristics of specifications but also appropriately reflects valuation elements in which relative environments of technically similar patents are taken into consideration, and to valuate a patent.
- a method of valuating a patent using a multiple regression model comprising: acquiring patent information; processing the patent information and separately performing a plurality of multiple regression analyses in which a plurality of key valuation elements preset for a valuation index are dependent variables; calculating a representative value of a plurality of regression coefficients for each independent variable of a plurality of multiple regression models calculated through the plurality of multiple regression analyses, and generating a valuation model for the valuation index by building a valuation model in which the calculated representative values are coefficients for the respective independent variables; obtaining information on an issued patent; and generating a quantified valuation index of the issued patent which is a valuation target using the generated valuation model.
- the method further comprises generating respective valuation models for a plurality of valuation indices, wherein the valuation indices include one or more of a degree of right, a degree of technology, and a degree of utilization.
- the separately performing of the plurality of multiple regression analyses comprises performing the multiple regression analyses, in which preset valuation elements are the independent variables of the multiple regression models, for the respective key valuation elements.
- the key valuation elements belong to the valuation elements, and a key valuation element is used as an independent variable of a multiple regression model for another key valuation element.
- the generating of the valuation model comprises calculating a weighted average or an arithmetic average of the plurality of regression coefficients as the representative value.
- valuation elements whose significance probabilities are a preset reference value or less are used in the multiple regression models
- the separately performing of the plurality of multiple regression analyses comprises performing a multicollinearity test among the valuation elements and excluding one or more valuation elements.
- a system for building a patent valuation model using a multiple regression model comprising: at least one processor; and at least one memory, wherein the at least one memory and the at least one processor store and execute instructions for causing the system to perform operations including: extracting valuation elements by processing acquired patent information; separately performing a plurality of multiple regression analyses in which a plurality of key valuation elements preset for a valuation index are dependent variables; calculating a representative value of a plurality of regression coefficients for each independent variable of a plurality of multiple regression models calculated through the plurality of multiple regression analyses; generating a valuation model for the valuation index by building a valuation model in which the calculated representative values are coefficients for the respective independent variables; and calculating a quantified valuation index of a patent which is a valuation target using the generated valuation model.
- the operations further include valuating a patent whose information has been acquired and storing a valuation result in the valuation result database (DB).
- DB valuation result database
- the operations further includes valuating at a preset point in time the patent whose information has been acquired and storing a valuation result in the valuation result DB.
- a method for building a patent valuation model using a multiple regression model including: acquiring patent information; processing the patent information and separately performing a plurality of multiple regression analyses in which a plurality of key valuation elements preset for a valuation index are dependent variables; and calculating a representative value of a plurality of regression coefficients for each independent variable of a plurality of multiple regression models calculated through the plurality of multiple regression analyses, and generating a valuation model for the valuation index by building a valuation model in which the calculated representative values are coefficients for the respective independent variables.
- FIG. 1 is an example diagram showing a schematic configuration of a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 2 is an example diagram showing a detailed configuration of a server in a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 3 is an example diagram showing operations of a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 4 is a flowchart illustrating a process of generating a valuation model in a method of valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 5 is a flowchart illustrating a process of valuating a patent in a method of valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 6 is an example diagram showing a detailed configuration of a server in a system for valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention
- FIG. 7 is a flowchart illustrating a process of valuating a patent in a method of valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention.
- FIG. 8 is a flowchart illustrating a process of providing a patent valuation service in a method of valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention.
- FIG. 1 is an example diagram showing a schematic configuration of a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention.
- the system for valuating a patent using a multiple regression model may be composed of at least one server 100 , which may be connected to a wired or wireless network and provide patent valuation results to a user device 200 .
- the server 100 may provide a valuation result of the patent. A detailed operation thereof will be described below.
- the server 100 may include a processor, a memory for storing and executing program data, a permanent storage section, a communication port for communicating with an external device, a user interface device, and the like.
- Methods implemented by software program modules or algorithms may be stored in computer-readable recording media as computer-readable codes or program instructions which can be executed by the processor.
- the computer-readable recording media may be distributed to computer systems connected via a network so that computer-readable codes may be stored and executed in a distributed manner.
- each block, unit, and/or module may be implemented by dedicated hardware or as a combination of dedicated hardware to perform some functions and a processor (e.g., one or more programmed processors and associated circuitry) to perform other functions.
- a processor e.g., one or more programmed processors and associated circuitry
- Each block, unit, and/or module of some exemplary embodiments may be physically separated into two or more interacting and discrete blocks, units, and/or modules without departing from the scope of the inventive concept. Further, blocks, units, and/or module of some exemplary embodiments may be physically combined into more complex blocks, units, and/or modules without departing from the scope of the inventive concept.
- FIG. 2 is an example diagram showing a detailed configuration of a server in a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention.
- the server 100 may include a patent information processor 110 , a multiple regression analysis processor 120 , a valuation model generating processor 130 , a valuation model database (DB) 140 , and a patent valuation processor 150 .
- these components may be distributed to one or more servers connected via a wired or wireless network.
- the patent information processor 110 may extract valuation elements by processing acquired patent information.
- the patent information processor 110 may collect patent information from an external data provider.
- the server 100 may include a data collector (not shown) which receives Korean or foreign (e.g., US) raw data from the external data provider.
- a data collector may physically include a network interface (a network interface card (NIC)) and may logically be a program serving as an application programming interface (API).
- NIC network interface card
- API application programming interface
- the patent information processor 110 may extract information from the acquired patent information and parse (or convert) the extracted information.
- the patent information processor 110 may extract information including a patent specification, bibliographic information, progress information, drawings, and the like, and the specification may be written in, for example, extensible markup language (XML). Therefore, it is possible to extract valuation elements by parsing the XML format.
- XML extensible markup language
- the server 100 may acquire patent information of a plurality of patents, and the patent information processor 110 may extract valuation elements from each patent and store extracted data in a DB (not shown).
- the acquired patent information may have been processed already (e.g., when valuation elements have been extracted and provided in advance).
- the patent information processor 110 may omit a process of extracting valuation elements.
- the multiple regression analysis processor 120 may build respective multiple regression models, in which a plurality of key valuation elements previously set for a valuation index among the valuation elements are dependent variables, and calculate regression coefficients of the plurality of multiple regression models for respective independent variables by performing multiple regression analyses. A detailed operation thereof will be described below.
- the valuation model generating processor 130 may calculate a representative value of regression coefficients of the plurality of multiple regression models calculated for each independent variable by the multiple regression analysis processor 120 and generate a valuation model for the valuation index. For example, a weighted average or an arithmetic average of the regression coefficients may be calculated as the representative value.
- the valuation model generating processor 130 may combine regression coefficients of the plurality of multiple regression analysis models for each independent variable into a weight average (or an arithmetic average) and generate (build) a valuation model for the valuation index. Also, the valuation model generating processor 130 may store the generated valuation model in the valuation model DB 140 so that patent valuation may be performed.
- the patent valuation processor 150 may calculate a quantified valuation index (e.g., a valuation score or a valuation grade) of a valuation target patent using the valuation model stored in the valuation model DB 140 . Specifically, it is possible to calculate a quantified valuation index of the corresponding patent by inputting information of the patent into the respective independent variables of the multiple regression analysis models which have been combined into weight averages (or arithmetic averages), or it is possible to calculate a representative value of valuations on the corresponding patent by combining quantified valuation indices, which will be described below.
- a quantified valuation index e.g., a valuation score or a valuation grade
- FIG. 3 is an example diagram showing operations of a system for valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention.
- the server 100 extracts valuation elements by refining and processing collected patent information, generates valuation models for respective valuation indices (or technical fields) through multiple regression analyses, and valuates the patent using the generated valuation models so that a user may be provided with a patent analysis service.
- FIG. 4 is a flowchart illustrating a process of generating a valuation model in a method of valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention
- FIG. 5 is a flowchart illustrating a process of valuating a patent in a method of valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention.
- a method of valuating a patent using a multiple regression model according to an exemplary embodiment of the present invention will be described with reference to FIGS. 4 and 5 .
- the server 100 acquires patent information first (S 300 ) and extracts valuation elements from the acquired patent information (S 310 ).
- the operation (S 310 ) of extracting valuation elements may be omitted.
- the server 100 performs multiple regression analyses for a plurality of key valuation elements of a valuation index (S 320 ).
- the server 100 may build a plurality of multiple regression models, in which each of a plurality of key valuation elements preset for the valuation index is a dependent variable and valuation elements are independent variables, and perform multiple regression analyses for the respective key valuation elements.
- the key valuation elements are included in the valuation elements, and multiple regression analyses are performed on the plurality of key valuation elements. For this reason, when multivariate analysis is used, it is not possible to use one key valuation element as an independent variable for another key valuation element. Therefore, in the present invention, general multivariate analysis is not used, but a plurality of multiple regression analysis equations are constructed to perform a multiple regression analysis in which each of a plurality of key valuation elements is a dependent variable.
- Equation 1 a plurality of multiple regression analysis equations as shown in Equation 1 below may be constructed to perform a regression analysis.
- y 1 ⁇ 0 1 + ⁇ 1 1 x 1 + ⁇ 2 1 x 2 + ⁇ 3 1 x 3 + . . . + ⁇ n 1 x n + ⁇ 1
- y denotes a multiple regression model for a key valuation element, and a subscript thereof denotes an order of a dependent variable (the key valuation element).
- x denotes independent variables.
- ⁇ 0 to ⁇ n denote regression coefficients, and ⁇ 0 among them denotes a constant.
- ⁇ denotes an error.
- superscripts denote orders of dependent variables, and subscripts denote orders of independent variables (valuation elements).
- the server 100 calculates a representative value of regression coefficients (including a constant) for each independent variable and generates a valuation model for the valuation index (S 330 ).
- a representative value of regression coefficients including a constant
- a valuation model for the valuation index S 330 .
- a weighted average or an arithmetic average of regression coefficients is calculated as a representative value so that a valuation model may be generated.
- a valuation model may be generated as shown in Equation 2 below.
- Y ( ⁇ 1 ⁇ 0 1 + ⁇ 2 ⁇ 0 2 + . . . ⁇ m ⁇ 0 m )+( ⁇ 1 ⁇ 1 1 + ⁇ 2 ⁇ 1 2 + . . . ⁇ m ⁇ 1 m )+ . . . +( ⁇ 1 ⁇ n 1 + ⁇ 2 ⁇ n 2 + . . . ⁇ m ⁇ n m ) x n
- Y denotes a quantified valuation index
- a denotes a weight and a subscript thereof denotes orders of dependent variables.
- a calculated representative value becomes a coefficient of an independent variable.
- each multiple regression equation may be constructed to use only valuation elements whose significance probabilities are a reference value or less. Such exclusion of valuation elements may be performed in real time during a multiple regression analysis process.
- the reference value of a significance probability is 0.1 or less and may be 0.05.
- valuation elements may be excluded through a multicollinearity test among the valuation elements.
- a valuation element excluded through the multicollinearity test among the valuation elements may be “the number of dependent claims.”
- valuation elements to be used as independent variables may be set in advance for each key valuation element, and a specific valuation element may be excluded in a manner in which a regression coefficient for a valuation element excluded from a specific key valuation element is fixed at 0 in the corresponding multiple regression equation.
- a method of valuating a patent using a multiple regression model may be configured to separately generate valuation models for a plurality of valuation indices.
- the valuation indices may include one or more of a degree of right, a degree of technology, and a degree of utilization.
- the degree of right denotes a degree to which a valuation target patent may maintain an exclusive position in patent disputes with third parties.
- the degree of technology denotes a degree to which a valuation target patent corresponds with technical trends and leads the technical trends.
- the degree of utilization denotes a degree to which a valuation target patent is used in business and a utilization probability of the valuation target patent.
- one or more of the fixed number of invalidation trials or inter partes reviews (IPRs) or post grant reviews (PGRs) proceeding in US Patent Trial and Appeal Board (PTAB), whether a divisional application or a continuation application has been made, and whether the valuation target patent has been involved in a patent infringement action (abbreviated to “infringement action” below) may be used as key valuation elements for the degree of right, one or more of whether a continuation application has been made, the total number of forward citations, and the rates of increase or decrease in patents of respective countries corresponding to a cooperative patent classification (CPC) level of the valuation target patent (e.g., a rate of increase or decrease in US patents in the case of US patent analysis) may be used as key valuation elements for the degree of technology, and one or more of whether a continuation application has been made, whether the valuation target patent has been involved in an infringement action, foreign family information (whether a
- valuation elements varying according to characteristics of patent laws and patent systems of individual countries may be taken into consideration.
- a right limitation procedure the number of demurrants, whether a divisional application has been made, and the total number of forward citations may be used as key valuation elements for valuating the degree of right
- one or more of the total number of forward citations, the number of demurrants, and the number of research papers among cited references may be used as key valuation elements for valuating the degree of technology
- one or more of whether a license has been granted, the number of demurrants, the number of first-entry countries for European patent registration, and a right limitation procedure may be used as key valuation elements for valuating the degree of utilization.
- the method of valuating a patent using a multiple regression model may be designed to use, as valuation elements, for example, a rate of increase or decrease in US patents of CPC levels, the number of interferences, the number of international patent classifications (IPCs), the number of IPRs and PGRs (fixed), the number of IPRs and PGRs (pending), the number of requests for continued examinations (RCEs), the number of reexaminations, the number of reissues, whether a continuation application has been made, the number of changes in patentees, the number of drawings included in a patent specification, lengths of independent claims included in the patent specification, the number of independent claims, a length of patent description, the number of inventors, whether a valuation target patent has been involved in an infringement action, the number of times that an annual registration has been made for the patent, whether a preferential examination has been requested, the number of research papers among preceding literatures (referred to as “cited references” below) cited by an examiner, an average
- valuation elements may be excluded from valuation elements, and in the case of a model which has the fixed number of IPRs and PGRs as a dependent variable, a rate of increase or decrease in US patents of CPC levels, the number of interferences, whether a continuation application has been made, the number of drawings, a length of patent description, an average age of cited patents, the number of times that information has been provided, an average depth of dependent claims, the number of series of claims, whether the valuation target patent is a standard essential patent, the number of foreign family countries, etc. may be excluded from valuation elements.
- the fixed number of IPRs and PGRs, the number of RCEs, the number of series of claims, etc. may be excluded from valuation elements.
- an average depth of dependent claims, the number of series of claims, etc. may be excluded from valuation elements.
- the total number of forward citations is a dependent variable, the number of times that information has been provided, etc. may be excluded from valuation elements.
- the fixed number of IPRs and PGRs, the number of interferences, the number of RCEs, the number of reexaminations, the number of times that information has been provided, the number of research papers among forward citations, etc. may be excluded from valuation elements.
- the fixed number of IPRs and PGRs, the number of IPRs and PGRs (pending), the number of interferences, the number of times that information has been provided, etc. may be excluded from valuation elements.
- the method of valuating a patent using a multiple regression model may be used to generate a valuation model for valuating patents of individual countries not only including European Union, US, and Korea but also including Japan, China, etc. in the world.
- the server 100 receives identification information of a patent which is a valuation target from the user device 200 as illustrated in FIG. 5 to provide a patent valuation service (S 400 ).
- the server 100 may receive an application number, a registration number, or the like of the valuation target patent as identification information.
- the server 100 calculates a quantified valuation index of the patent using the valuation model generated in operation S 330 of FIG. 4 (S 410 ).
- the server 100 may acquire valuation elements of the valuation target patent and calculate a corresponding quantified valuation index by putting the acquired valuation elements into the valuation model.
- the server 100 may calculate a plurality of quantified valuation indices (e.g., the degree of right, the degree of technology, and the degree of utilization) of the valuation target patent using valuation models for a plurality of valuation indices.
- the server 100 calculates a representative value of the plurality of quantified valuation indices as a representative valuation value of the patent (S 420 ).
- the server 100 may calculate a representative value (e.g., a weighted average or an arithmetic average) of the calculated degrees of right, technology, and utilization and determine a grade of the patent through the calculated value.
- FIG. 6 is an example diagram showing a detailed configuration of a server in a system for valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention.
- FIG. 7 is a flowchart illustrating a process of valuating a patent in a method of valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention
- FIG. 8 is a flowchart illustrating a process of providing a patent valuation service in a method of valuating a patent using a multiple regression model according to another exemplary embodiment of the present invention.
- the method of valuating a patent using a multiple regression model according to the other exemplary embodiment of the present invention will be described with reference to FIGS. 6 to 8 .
- a server 100 in the system for valuating a patent may include a valuation result DB 160 in addition to a patent information processor 110 , a multiple regression analysis processor 120 , a valuation model generating processor 130 , a valuation model DB 140 , and a patent valuation processor 150 .
- Configurations and operations of the patent information processor 110 , the multiple regression analysis processor 120 , the valuation model generating processor 130 , the valuation model DB 140 , and the patent valuation processor 150 may be the same as those described with reference to FIG. 2 .
- the patent valuation processor 150 may perform patent valuation when patent valuation is requested through a user device 200 and may also valuate collected patents automatically and store valuation results in the valuation result DB 160 . In this case, when patent valuation is requested through the user device 200 , a valuation result previously stored in the valuation result DB 160 is extracted and output so that a time required to output the valuation result in response to the valuation request may be minimized.
- the patent valuation processor 150 may valuate collected patents again at a preset date and time and update the valuation results stored in the valuation result DB 160 . This is because a valuation result of a patent may vary according to valuation time points.
- operations S 600 to S 630 may be the same as those described with reference to FIG. 4 .
- the server 100 valuates a patent acquired in operation S 600 using a valuation model generated in operation S 630 (S 640 ) and stores a valuation result (S 650 ).
- the server 100 may not only build a valuation model using collected patents but may also valuate the collected patents and store valuation results before a user's request.
- the server 100 reads and transmits a stored valuation result to the user device 200 (S 710 ).
- the patent may not be valuated in real time, and the previously stored patent valuation result may be provided.
- a system and method for building a patent valuation model using a multiple regression model and a system and method for valuating a patent using a multiple regression model make it possible to build a multiple regression model for each of a plurality of key valuation elements and generate a valuation model for a patent valuation index by combining a plurality of regression coefficients of the multiple regression models. Therefore, it is possible to appropriately reflect valuation elements in which relative environments of technically similar patents are taken into consideration while reflecting structural characteristics of patent specifications.
- a system and method for building a patent valuation model using a multiple regression model and a system and method for valuating a patent using a multiple regression model make it possible to valuate many patents rapidly and inexpensively on the basis of objective evaluation criteria.
- a system and method for building a patent valuation model using a multiple regression model and a system and method for valuating a patent using a multiple regression model make it possible to generate valuation information for each of a plurality of valuation items for one patent.
Abstract
Description
y 1=β0 1+β1 1 x 1+β2 1 x 2+β3 1 x 3+ . . . +βn 1 x n+ε1
y 2=β0 2+β1 2 x 1+β2 2 x 2+β3 2 x 3+ . . . +βn 2 x n+ε2
y 3=β0 3+β1 3 x 1+β2 3 x 2+β3 3 x 3+ . . . +βn 3 x n+ε3
. . .
y m=β0 m+β1 m x 1+β2 m x 2+β3 m x 3+ . . . +βn m x n+εm
Y=(α1β0 1+α2β0 2+ . . . αmβ0 m)+(α1β1 1+α2β1 2+ . . . αmβ1 m)+ . . . +(α1βn 1+α2βn 2+ . . . αmβn m)x n
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JP2022025339A (en) | 2020-07-29 | 2022-02-10 | アスタミューゼ株式会社 | Information processing apparatus, information processing method, and program |
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CN109840670A (en) | 2019-06-04 |
US20190163440A1 (en) | 2019-05-30 |
JP6707612B2 (en) | 2020-06-10 |
EP3489885A1 (en) | 2019-05-29 |
KR101932517B1 (en) | 2018-12-26 |
EP4033443A1 (en) | 2022-07-27 |
JP2019096327A (en) | 2019-06-20 |
JP2019096325A (en) | 2019-06-20 |
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